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  1.  42
    Systematic Observation of an Expert Driver's Gaze Strategy—An On-Road Case Study.Otto Lappi, Paavo Rinkkala & Jami Pekkanen - 2017 - Frontiers in Psychology 8.
  2.  12
    Looking at the Road When Driving Around Bends: Influence of Vehicle Automation and Speed.Damien Schnebelen, Otto Lappi, Callum Mole, Jami Pekkanen & Franck Mars - 2019 - Frontiers in Psychology 10.
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  3.  18
    Action control, forward models and expected rewards: representations in reinforcement learning.Jami Pekkanen, Jesse Kuokkanen, Otto Lappi & Anna-Mari Rusanen - 2021 - Synthese 199 (5-6):14017-14033.
    The fundamental cognitive problem for active organisms is to decide what to do next in a changing environment. In this article, we analyze motor and action control in computational models that utilize reinforcement learning (RL) algorithms. In reinforcement learning, action control is governed by an action selection policy that maximizes the expected future reward in light of a predictive world model. In this paper we argue that RL provides a way to explicate the so-called action-oriented views of cognitive systems in (...)
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  4.  17
    From Fly Detectors to Action Control: Representations in Reinforcement Learning.Anna-Mari Rusanen, Otto Lappi, Jami Pekkanen & Jesse Kuokkanen - 2021 - Philosophy of Science 88 (5):1045-1054.
    According to radical enactivists, cognitive sciences should abandon the representational framework. Perceptuomotor cognition and action control are often provided as paradigmatic examples of nonrepresentational cognitive phenomena. In this article, we illustrate how motor and action control are studied in research that uses reinforcement learning algorithms. Crucially, this approach can be given a representational interpretation. Hence, reinforcement learning provides a way to explicate action-oriented views of cognitive systems in a representational way.
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